Assessing the performance of Microsoft Copilot, GPT-4 and Google Gemini in ophthalmology.

Journal: Canadian journal of ophthalmology. Journal canadien d'ophtalmologie
Published Date: Feb 4, 2025

Abstract

OBJECTIVE: To evaluate the performance of large language models (LLMs), specifically Microsoft Copilot, GPT-4 (GPT-4o and GPT-4o mini), and Google Gemini (Gemini and Gemini Advanced), in answering ophthalmological questions and assessing the impact of prompting techniques on their accuracy.

Authors

  • Meziane Silhadi
    Faculty of Medicine, University of Montreal, Montreal, QC, Canada.
  • Wissam B Nassrallah
    Department of Ophthalmology, Centre Hospitalier de l'Université de Montréal, Montreal, QC, Canada.
  • David Mikhail
    Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
  • Daniel Milad
    Faculty of Medicine, University of Montreal, Montreal, QC, Canada; Department of Ophthalmology, Centre Hospitalier de l'Université de Montréal, Montreal, QC, Canada.
  • Mona Harissi-Dagher
    Faculty of Medicine, University of Montreal, Montreal, QC, Canada; Department of Ophthalmology, Centre Hospitalier de l'Université de Montréal, Montreal, QC, Canada. Electronic address: monal.harissi.dagher@umontreal.ca.

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